Planning with Incrementally Created Graphs

A framework for planning algorithms that is both optimal and complete will be presented. The algorithm allows for the planning of optimal paths through a multi-level hierarchy of annotated graph spaces. A rich world model that contains multi-resolution attributes, costs, and predicates controls the integrated incremental construction and evaluation of the planning graph in dynamic environments. The properties of this framework are proven and a number of example problem domains are presented that show how this framework can incorporate both hard and soft constraints during both graph construction and arc evaluation.